Community tutorials#
This is a guide to many pandas tutorials by the community, geared mainly for new users.
pandas cookbook by Julia Evans#
The goal of this 2015 cookbook (byJulia Evans) is togive you some concrete examples for getting started with pandas. Theseare examples with real-world data, and all the bugs and weirdness thatentails.For the table of contents, see thepandas-cookbook GitHubrepository.
pandas workshop by Stefanie Molin#
An introductory workshop byStefanie Molindesigned to quickly get you up to speed with pandas using real-world datasets.It covers getting started with pandas, data wrangling, and data visualization(with some exposure to matplotlib and seaborn). Thepandas-workshop GitHub repositoryfeatures detailed environment setup instructions (including a Binder environment),slides and notebooks for following along, and exercises to practice the concepts.There is also a lab with new exercises on a dataset not covered in the workshop foradditional practice.
Learn pandas by Hernan Rojas#
A set of lesson for new pandas users:https://bitbucket.org/hrojas/learn-pandas
Practical data analysis with Python#
Thisguide is an introduction to the data analysis process using the Python data ecosystem and an interesting open dataset.There are four sections covering selected topics asmunging data,aggregating data,visualizing dataandtime series.
Exercises for new users#
Practice your skills with real data sets and exercises.For more resources, please visit the mainrepository.
Modern pandas#
Tutorial series written in 2016 byTom Augspurger.The source may be found in the GitHub repositoryTomAugspurger/effective-pandas.
Excel charts with pandas, vincent and xlsxwriter#
Joyful pandas#
A tutorial written in Chinese by Yuanhao Geng. It covers the basic operationsfor NumPy and pandas, 4 main data manipulation methods (including indexing, groupby, reshapingand concatenation) and 4 main data types (including missing data, string data, categoricaldata and time series data). At the end of each chapter, corresponding exercises are posted.All the datasets and related materials can be found in the GitHub repositorydatawhalechina/joyful-pandas.
Video tutorials#
Pandas From The Ground Up(2015) (2:24)GitHub repo
Introduction Into Pandas(2016) (1:28)GitHub repo
Pandas: .head() to .tail()(2016) (1:26)GitHub repo
Data analysis in Python with pandas(2016-2018)GitHub repo andJupyter Notebook
Best practices with pandas(2018)GitHub repo andJupyter Notebook